1. Field of the Invention
The present invention relates to color correction of motion pictures captured by a plurality of cameras.
2. Description of the Related Art
In a multi-view camera system, a plurality of cameras, which are located at different positions, respectively take moving pictures, each of which has a plurality of frames or images for the same objects. Normally, the color of images taken by a camera is different from one taken by other cameras due to several factors, for example, direction of light source or characteristic variation of cameras. Therefore color correction is required, and various methods have been proposed.
For example, following three documents respectively disclose color correction methods using color pattern board, and histogram matching for some application, e.g. multi-view coding.    (1) N. Joshi, et al., “Automatic Color Calibration for Large Camera Arrays”, UCSD CSE Technical Report, CS2005-0821    (2) K. Sohn, et al., “H.264/AVC-compatible Multi-view Video Coding”, ISO/IEC JTC1/SC29/WG11 M12874    (3) Y. Chen, et al., “Ni Luminance and Chrominance Correction for Multi-View Video Using Simplified Color Error Model”, PCS2006
In document (1), color pattern boards are used to obtain the corresponding intensities between a captured image by a camera and actual color intensities. The document (1) introduces a method to generate a linear transformation equation based on linear least square matching in the format of a 3×3 matrix or a general polynomial transformation equation. The color of each pixel in the captured image by a camera is corrected by the equation.
In document (2), color and luminance are compensated using an average and a variance in a block. This method cannot be directly used for general purpose color correction.
In document (3), the linear transformation is generated for YUV channels, the coefficients of which were searched by iterative linear transformation.
Correction using color pattern board is not suitable for outdoor and wide space coverage of multicamera systems, since providing a color pattern board is not easy. In addition, all intensities, e.g. reflection of light from a window on the board or dark areas, are blindly detected. Therefore it is impossible for some cases to capture whole intensities using the color pattern board. Furthermore, these approaches do not consider the geometrical characteristic of multicamera systems.
Further, the histogram based correction method cannot handle occlusion areas, so that the quality of correction depends on these areas.
On the other hand, another method is proposed in a following document.    (4) K. Yamamoto, et al., “Colour Correction for Multiple-camera System by using Correspondences”, The Journal of The Institute of Image Information and Television Engineers, Vol. 61, No. 2, pp. 1 to 9, 2007
In the method, one camera takes reference image, and other cameras take target images. Then corresponding pixel pairs between the reference image and the target image are searched, and then each pixel in the target image is corrected by the corresponding pixel in the reference image. Thus, the problem of the color pattern board method can be avoided.
However, the quality of color correction becomes worse with increasing a distance between the camera for reference images and the camera for target images. Moreover, if there is an occlusion in a reference image, color correction of target image pixels, which are not shown in the reference image, is not possible.